CL4.11 | Modelling and Observational Constraints for Earth System Feedbacks and Tipping Points
EDI
Modelling and Observational Constraints for Earth System Feedbacks and Tipping Points
Convener: Paul RitchieECSECS | Co-conveners: Rebecca VarneyECSECS, Sabrina ZechlauECSECS, Ruth ChapmanECSECS, Hassan AlkhayuonECSECS
Orals
| Mon, 24 Apr, 16:15–17:55 (CEST)
 
Room 0.49/50
Posters on site
| Attendance Tue, 25 Apr, 08:30–10:15 (CEST)
 
Hall X5
Posters virtual
| Attendance Tue, 25 Apr, 08:30–10:15 (CEST)
 
vHall CL
Orals |
Mon, 16:15
Tue, 08:30
Tue, 08:30
This session hopes to bring together Climate Scientists, Mathematicians and Ecologists to answer key questions around the relationships between the variability and sensitivity of the Earth System and its subcomponents. In particular, this session will discuss observational constraints and tipping points for Earth System feedbacks.

State-of-the-art Earth System Models feature wide ranges of projected future change arising from uncertainties in both forcing factors (such as the climatic effects of anthropogenic aerosols) and feedbacks (such as those due to clouds or the carbon cycle). It is vital that we reduce these uncertainties to provide better information for climate change mitigation and adaptation. Constraints provide a method of reducing projection uncertainty, often by investigating relationships between temporal or spatial sensitivity and variability (such as Emergent Constraints). Tipping points are typically associated with some external forcing exceeding a critical level causing a system to transition abruptly to an alternative, and often less desirable, state. However, the role of temporal and spatial scales requires careful consideration given the possibilities of other tipping phenomena such as rate-induced tipping, overshoots and spatial cascades.

The aim of this session is to cover exciting new work on climate tipping points, and observational and emergent constraints on Earth System feedbacks, as well as to promote cross-fertilisation of ideas between these two important emerging topics in climate science. We invite contributions from a range of studies investigating variability and sensitivity of the Earth System, focussing on either constraining Earth System sensitivities or modelling/theoretical studies of tipping points.

Orals: Mon, 24 Apr | Room 0.49/50

Chairpersons: Paul Ritchie, Rebecca Varney
16:15–16:25
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EGU23-3204
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solicited
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Highlight
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On-site presentation
Anna von der Heydt

The currently ongoing climate change and the debate about possible measures to be taken to limit the consequences of climate change, requires to know and understand the future response of the climate system to greenhouse gas emissions. Classical measures of climate change such as the Equilibrium Climate Sensitivity (ECS) are inherently linear and unable to account for abrupt transitions due to (interacting) tipping elements.

In this presentation I will discuss more general notions of climate sensitivity defined on a climate attractor that can be useful in understanding the response of a climate state to changes in radiative forcing. For example, a climate state close to a tipping point will have a degenerate linear response to perturbations, which can be associated with extreme values of the ECS. While many identified tipping elements in the climate system are regional and may have no direct impact on the global mean temperature, cascades of tipping elements can potentially have an impact, initiated by the threshold of the leading tipping element in a cascade.

How to cite: von der Heydt, A.: Dynamical systems approaches to climate response and climate tipping, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3204, https://doi.org/10.5194/egusphere-egu23-3204, 2023.

16:25–16:35
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EGU23-4493
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On-site presentation
Nicola Scafetta

Climatological risk assessments are currently based on simulations for the twenty-first century made using global climate models (GCMs) from the sixth Coupled Model Intercomparison Project Phases (CMIP6) by adopting several hypothetical shared socioeconomic pathways (SSPs) emission scenarios. However, there are large differences in the climatic sensitivity to atmospheric CO2 increase amongst the available climate models: for example, for the CMIP6 GCM the ECS varies between 1.8°C and 5.7°C and the TCR varies from 1.2°C to 2.8°C. There is also mounting evidence that many GCMs are operating "too hot" and are therefore unreliable for informing climate change policy for the future. Here, we assess the performance of 41 CMIP6 GCMs by ranking and comparing them using their literature-provided estimates for the equilibrium climate sensitivity (ECS) and transient climate response (TCR). We discover that the GCM sub-ensemble that performs the best in hindcasting the warming from 1980 to 2021 is that made of the GCMs with ECS ranging between 1.8 and 3.0 °C and TCR ranging between 1.2 and 1.8 °C. A total of 17 models make up this GCM sub-ensemble. The predicted warming of these models for the mid-term (2041-2060) period is 1.5–2.5°C relative to the preindustrial period (1850-1900) according to various SSP scenarios. Thus, the global aggregated impact and risk assessments assuming low to no adaptation appear, therefore, moderate, which also implies that adaptation policies may be adequate to address any unfavorable effects of future climate changes. We also discuss the additional uncertainties surrounding the warming of the Earth's surface temperature by comparing several temperature reconstructions and the warming differences observed between land and ocean to discuss the possibility that ECS and TRC could be furtherly constrained.

Main references:

Scafetta N (2022) Advanced testing of low, medium, and high ECS CMIP6 GCM simulations versus ERA5-T2m. Geophys Res Lett 49:e2022GL097716. https://doi.org/10.1029/2022GL097716

Scafetta, N. CMIP6 GCM ensemble members versus global surface temperatures. Clim Dyn (2022). https://doi.org/10.1007/s00382-022-06493-w

How to cite: Scafetta, N.: Constraining ECS and TCR for 21st century for temperature forecasts and risk assessments by comparing the CMIP6 GCM simulations versus global surface temperature records, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4493, https://doi.org/10.5194/egusphere-egu23-4493, 2023.

16:35–16:45
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EGU23-3905
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On-site presentation
Kieran Mulchrone, Eoin O'Sullivan, and Sebastian Wieczorek

The Arctic is the fastest warming region on Earth. Understanding how a rapidly changing climate change impacts Arctic systems is therefore an important challenge. This is the basis of the `Compost-Bomb' instability, a theorized runaway heating of northern latitude peat soils when atmospheric temperature rises faster than some critical rate, first proposed in [Luke & Cox, European Journal of Soil Science (2011), 62.1] and analysed in [Wieczorek et al, Proceedings of the Royal Society A (2011), 467.2129]. The Compost Bomb instability was one of the first examples of what is known as Rate-induced tipping or R-tipping.

The key trigger for the compost bomb instability is heat produced by microbial respiration. Here, the original soil carbon and temperature model of Luke & Cox is augmented with a non-monotone microbial respiration function, for a more realistic representation of the process. This gives rise to a meta-stable state, reproducing the results of [Khvorostyanov et al, Tellus (2008), 60B] where a complex PDE model is used. Two non-autonomous climate forcings are examined: (i) a rise in mean air temperature over decades (ii) a short-lived extreme weather event, with the rate-induced compost bomb observed in each. Using techniques of compactification, singular perturbation theory and desingularisation, we reduce the R-tipping problem to one of heteroclinic orbits, uncovering the tipping mechanism for each climate change scenario.

How to cite: Mulchrone, K., O'Sullivan, E., and Wieczorek, S.: Rate-Induced Tipping of the Compost Bomb: Sizzling Summers, Heteroclinic Canards and Metastable Zombie Fires, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3905, https://doi.org/10.5194/egusphere-egu23-3905, 2023.

16:45–16:55
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EGU23-7869
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ECS
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On-site presentation
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Sophie Wilkinson, Peer Nowack, and Manoj Joshi

Knowledge about future global and regional warming is essential for effective adaptation planning and our current temperature projections are based on the output of global climate models (GCMs). Although GCMs agree on the direction of change, there are still significant discrepancies in the magnitude of the projected response1. 

Here we develop a novel method2,3 for constraining uncertainty in future regional temperature projections based on the predictions of an observationally trained machine learning algorithm, Ridge-ERA5. Ridge-ERA5 - a Ridge regression model4- learns coefficients to represent observed relationships between daily temperature anomalies and a selection of thermodynamic and dynamical variables in the ECMWF Re-Analysis (ERA) 5 dataset5. Climate-invariance of the Ridge relationships is demonstrated in a perfect model framework: we train a set of 23 Ridge-CMIP models on historical data of the Coupled Model Intercomparison Project (CMIP) phase 66 and evaluate their predictions using future scenario data from the most extreme future emissions pathway, SSP 5-8.5.  

Combining the historically constrained Ridge-ERA5 coefficients with normalised inputs from CMIP6 future climate change simulations forms the basis of a new methodology to derive observational constraints on regional climate change. For daily, regional (2°x2°), summer temperatures across the Northern Hemisphere, the Ridge-ERA5 observations-based constraint implies, for example, that a group of higher sensitivity CMIP6 models is inconsistent with observational evidence (including in Eastern, West & Central, and Northern Europe) potentially suggesting that the sensitivity of these models is indeed too high7,8. A key advantage of our new method is the ability to constrain regional projections at very high – daily – temporal resolution which includes extreme events such as heatwaves. 

 

1) Brient, F. (2019) Reducing Uncertainties in Climate Projections with Emergent Constraints: Concepts, Examples and Prospects. Advances in Atmospheric Sciences 2020 37:1, 37(1), pp. 1–15. 

2) Ceppi, P. and Nowack, P. (2021) Observational evidence that cloud feedback amplifies global warming. PNAS, 118(30). 

3) Nowack, P. et al. An observational constraint on the uncertainty in stratospheric water vapour projections. (in review) 

4) Hoerl, A. E. and Kennard, R. W. (1970) Ridge Regression: Applications to Nonorthogonal Problems. Technometrics, 12(1), pp. 69–82.  

5) Hersbach, H. et al. (2020) The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), pp. 1999–2049.  

6) Eyring, V. et al. (2016) Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geoscientific Model Development, 9(5), pp. 1937–1958.  

7) Zelinka, M. D. et al. (2020) Causes of Higher Climate Sensitivity in CMIP6 Models. Geophysical Research Letters, 47(1). 

8) Zhu, J., Poulsen, C. J. and Otto-Bliesner, B. L. (2020) High climate sensitivity in CMIP6 model not supported by paleoclimate. Nature Climate Change 2020 10:5, 10(5), pp. 378–379. 

How to cite: Wilkinson, S., Nowack, P., and Joshi, M.: Observations-based machine learning model constrains uncertainty in future regional warming projections., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7869, https://doi.org/10.5194/egusphere-egu23-7869, 2023.

16:55–17:05
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EGU23-6055
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On-site presentation
Ashwin K Seshadri and David Stainforth

Low-order coupled models of the atmosphere and ocean can illuminate the role of weather-climate interactions in long-term climate prediction. An important example is models that bring together the interplay between the Atlantic meridional overturning circulation (AMOC) with mid-latitude quasi-geostrophic dynamics of the atmosphere, as in the coupled model introduced by Van Veen et al (2001). In such models, the AMOC can transition from its present thermally driven to a much weaker salinity-driven state, through a tipping point. We show using these coupled models that, for scenarios with intermediate forcing between a strong and weak circulation, the long-term evolution shows extreme sensitivity to initial conditions, due to the appearance of riddled basins of attraction. The literature on dynamical systems has extensively examined such dynamics when two distinct basins of attraction are riddled, that is any small part of one attractor’s basin also includes a piece of the other. Moreover, in the presence of feedback from the atmosphere to the ocean, initial atmospheric conditions are amplified to the extent that long-term prediction in these models is inhibited by the finite precision at which the atmospheric state is known. We propose to describe the various facets of this phenomenon and consider the lessons for understanding and predicting long-term climate (in our case, thermohaline circulation), given initial state uncertainty. Furthermore, the resulting challenges of long-term prediction are not necessarily ameliorated by the real-world asymmetries in the model. When the relevant symmetries that yield riddled basins are broken through perturbations to the vector fields, the asymptotic dynamics become perfectly predictable given the initial conditions; however, long-term uncertainties in the transient state (strong vs weak circulation) persist for centuries, owing to ocean timescales.

 

How to cite: Seshadri, A. K. and Stainforth, D.: Challenges of long-term AMOC prediction due to riddled basins in coupled atmosphere-ocean models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6055, https://doi.org/10.5194/egusphere-egu23-6055, 2023.

17:05–17:15
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EGU23-13608
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On-site presentation
Olivia Ferguglia, Elisa Palazzi, and Jost von Hardenberg

An Emergent Constraint (EC) is a physically-explainable relationship between model simulations of a past climate variable (predictor) and projections of a future climate variable (predictand). By constraining the predictor through observations, it is possible to narrow future model projections, if a significant correlation between the predictor and the predictand exists. In our work, the EC technique has been applied to the analysis of precipitation and precipitation extremes, variables that are strongly affected by model uncertainties and still insufficiently analyzed in the context of ECs. One of the main challenges in determining an EC is establishing if the relationship found is physically meaningful and if it is robust to changes in the composition of the model ensemble. Four ECs already documented in the literature and so far tested only with CMIP3 or CMIP5, have been reconsidered in our study. Their existence and robustness are evaluated by developing a systematic methodology that involves different subsets and different scenarios of CMIP5 and CMIP6 models, verifying if an EC found in CMIP3/CMIP5 is still present in the most recent ensemble and assessing its sensitivity to the detailed ensemble composition. Three out of the four ECs considered in our work did not pass the test, being robust in CMIP5 but not in CMIP6, or (in one case) being not robust in both CMIP5 and CMIP6. Only one EC is verified and robust in both model ensembles. These results show the difficulty of identifying robust precipitation ECs and cast doubts on the usability of such ECs as a tool to  reduce uncertainties in future projections of precipitation change. At the same time, this work highlights the importance of the EC technique  as a way to improve our understanding  of climate phenomena and their drivers and to investigate precipitation-related feedbacks, providing evidence of connections between precipitation and different climate variables. This observation lays the path to further explore original ECs.

How to cite: Ferguglia, O., Palazzi, E., and von Hardenberg, J.: Evaluation of Precipitation Emergent Constraints in CMIP5 and CMIP6, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13608, https://doi.org/10.5194/egusphere-egu23-13608, 2023.

17:15–17:25
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EGU23-6484
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ECS
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On-site presentation
Lilian Vanderveken, Marina Martínez Montero, and Michel Crucifix

Vegetation in semi-arid regions has adapted to low rainfall by organizing itself in patterns, which can be described by reaction-diffusion equations that include local positive feedback (e.g. infiltration) and non-local mitigation (e.g. lateral water flow). This allows the vegetation to survive in lower rainfall conditions and creates multiple stable states, meaning that for a fixed amount of rainfall, the vegetation can exist in different patterns. It is possible to identify these different equilibrium states and to create a bifurcation diagram for the model.
As the climate changes, there is likely to be a shift in the rainfall patterns in the Sahel, although it is not yet clear if there will be an increase or decrease in precipitation. In this context, we use the vegetation pattern model and its bifurcation diagram to understand how it will respond to slow and fast changes in rainfall, and explore the possibility of rate-induced tipping (R-tipping). 
On the other hand, rainfall, land use and fires have a stochastic component, which we represent by adding two types of noise to the system: homogeneous and heterogeneous. This noise can cause a switch from one stable equilibrium to another, known as N-tipping, depending on the type of noise applied. The vegetation pattern is more stable to homogeneous noise than heterogeneous, but when it tips the homogeneous noise kill all the vegetation.
Understanding how patterned systems respond to changing environments and noise is critical for predicting the future evolution of various patterned systems globally, not just vegetation in the Sahel.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme (grant no. 820970). 

How to cite: Vanderveken, L., Martínez Montero, M., and Crucifix, M.: R-tipping and N-tipping in a vegetation pattern model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6484, https://doi.org/10.5194/egusphere-egu23-6484, 2023.

17:25–17:35
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EGU23-10784
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On-site presentation
In-Hong Park and Sang-Wook Yeh

The North Atlantic is a pacemaker of global climate through the Atlantic meridional overturning circulation (AMOC) and a large anthropogenic carbon uptake. Removal of anthropogenic carbon in the atmosphere by the ocean is key mechanism for modulating warming rate of globe. But, there is a large uncertainty in climate models for simulating AMOC and anthropogenic carbon uptake. To reduce the uncertainties in anthropogenic carbon uptake and its associated Northern Hemisphere surface warming, here we apply an emergent constraint. Sea surface salinity is often used to represent ocean circulations through its strong relationship with ocean density. The results suggest that the present-day sea surface salinity in the North Atlantic subpolar region constrains the future warming of the Northern Hemisphere by modulating anthropogenic carbon uptake in the North Atlantic. Models that generate a present-day higher SSS in the North Atlantic subpolar region systematically tend to a greater uptake of anthropogenic carbon, resulting in a slower warming in the Northern Hemisphere.

How to cite: Park, I.-H. and Yeh, S.-W.: North Atlantic carbon uptake modulates warming rate of the future Northern Hemisphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10784, https://doi.org/10.5194/egusphere-egu23-10784, 2023.

17:35–17:45
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EGU23-12523
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On-site presentation
Aurélien Ribes and Saïd Qasmi

We describe a new statistical method to narrow uncertainty on estimates of past and climate change. Our approach can be viewed as an adaptation of Kalman Filtering, or Kriging, for Climate Change. The definition of what we call "signal" and "noise" are different from those used in typical weather forecasting systems, but the formalism is pretty similar, and estimation of the "model error" and "observational error" covariance matrices play a central role.


This approach allows us to simultaneously constrain projections, metrics of sensitivity, and to assess human influence on the past climate (attribution). It provides a consistent picture of on-going changes, through merging model simulations and observations in a Bayesian fashion. Cross-validation suggests that our method produces robust results and is not overconfident.


Beyond GSAT results, I will focus on application of this method to narrow uncertainty on regional or local scale warming -- which is a step forward from the AR6. Even at the local scale, we find that observational constraints narrow uncertainty on future warming, and that local observations provide useful information. The case of France will be used as an illustrative example, then I'll describe local results worldwide and show how they constrain warming patterns. I will briefly browse other applications, including some related to the water cycle, and discuss implications of this work. 

How to cite: Ribes, A. and Qasmi, S.: A Kalman Filtering approach to reduce uncertainty on global and regional climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12523, https://doi.org/10.5194/egusphere-egu23-12523, 2023.

17:45–17:55
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EGU23-4917
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solicited
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Highlight
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On-site presentation
Niklas Boers

Some components of the Earth system could change their state abruptly in response to a warming atmosphere and associated changes in climate conditions. This possibility has been recognized as one of the greatest potential threats associated with anthropogenic climate change. Examples  include the Atlantic Meridional Overturning Circulation, the polar ice sheets, the Amazon rainforest, and possibly the tropical monsoon systems.  The empirical evidence for abrupt climate transitions comes from paleoclimate proxy records, but also in observational records, signs of stability loss for some of the major tipping elements have been suggested. Here we explain some of the key theoretical concepts suggesting that tipping events may happen under ongoing climate change and summarize the empirical evidence for stability loss in some Earth system components with focus on candidates for future abrupt transitions. We argue that the critical forcing levels and rates are subject to large uncertainties and hence difficult to prdict. Improvements will require combining information from paleoclimate records, simulations with a hierarchy of models, and from observation-based data.

How to cite: Boers, N.: Theoretical and observational evidence for climate tipping points, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4917, https://doi.org/10.5194/egusphere-egu23-4917, 2023.

Posters on site: Tue, 25 Apr, 08:30–10:15 | Hall X5

Chairpersons: Hassan Alkhayuon, Sabrina Zechlau, Rebecca Varney
X5.228
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EGU23-17365
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solicited
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Highlight
Manuel Schlund, Sabrina Zechlau, Peter Cox, Pierre Friedlingstein, and Veronika Eyring

Emergent constraints help to better understand Earth system processes in a changing climate and to constrain future climate projections. Here, we analyze the robustness of two previously found emergent constraints on carbon cycle feedbacks using models from the Coupled Model Intercomparison Project (CMIP) of Phases 5 and 6. First, an emergent constraint on the carbon-climate feedback is evaluated, which is found to be robust regarding the choice of model ensemble. For the combined CMIP5 and CMIP6 ensembles, the sensitivity of tropical land carbon uptake to tropical warming is constrained to −37 ± 14 GtC/K. Second, we analyze an emergent constraint on the carbon-concentration feedback. This emergent constraint (originally derived from the CMIP5 models) is not evident in the CMIP6 ensemble. This is in part because the historical increase in the amplitude of the CO2 seasonal cycle is more accurately simulated in CMIP6, such that the models are all now close to the observational constraint.

How to cite: Schlund, M., Zechlau, S., Cox, P., Friedlingstein, P., and Eyring, V.: Do Emergent Constraints on Carbon Cycle Feedbacks hold in CMIP6?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17365, https://doi.org/10.5194/egusphere-egu23-17365, 2023.

X5.229
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EGU23-7393
Peter Cox, Mark Williamson, Joe Clarke, Chris Huntingford, and Paul Ritchie

Studies of the observed record of global warming suggest that the Earth’s climate sensitivity is at the lower end of the range produced by the CMIP6 Earth System Models (Jimenez and Mauritsen, 2019; Nijsse et al., 2020; Tokarska et al., 2020). However, studies based on top-of-the-atmosphere fluxes often suggest the opposite (Brown et al., 2017; Sherwood et al., 2020).

Earthshine estimates (Goode et al., 2021) and satellite measurements of the planetary albedo from CERES (Loeb et al., 2018) both indicate that the Earth has darkened significantly over the past two decades. Planetary darkening is also simulated in CMIP6 historical simulations , but the models with the highest climate sensitivities tend to fit the observed decline in planetary albedo much better. Observed planetary darkening therefore favours higher climate sensitivities, but constraints based on ground-based global warming records favour lower climate senstivities.

We explore this apparent paradox by calculating the contributions to changes in global warming that arise from diagnosable changes in planetary albedo and effective global emissivity, in both models and observational records. Differences between low and high sensitivity models are found to be predominantly due to the rate at which the modelled planetary albedo declines, which can in principle be due to a combination of forcing and feedbacks. However, planetary darkening in higher sensitivity models is primarily due to reductions in cloud cover, which results in a positive SW cloud feedback.

By contrast, the planetary darkening seen in the CERES satellite record is driven not by reductions in cloud cover, but instead by the darkening of clouds, and to a lesser extent by the darkening of clear skies. This suggest that darkening in CERES is driven by reductions in aerosols, which leads to reductions in negative aerosol forcing.  Planetary darkening in CERES therefore seems to be due primarily to changes in aerosol forcing.

Our proposed resolution to ‘The paradox of the darkening planet and the Earth’s climate sensitivity’ is therefore that climate sensitivity is indeed towards the lower end of the CMIP6 model range (as suggested by observed records of global warming), and that higher sensitivity models get the rate of planetary darkening ‘right’ but by the wrong mechanism (i.e. as a cloud forcing rather than as an aerosol feedback).  We will back this up by comparing the spatial patterns of planetary albedo change from models and the CERES satellite data, and finish by discussing possible implications for the time-varying aerosol precursor fields that are used to drive the CMIP6 simulations.

How to cite: Cox, P., Williamson, M., Clarke, J., Huntingford, C., and Ritchie, P.: The paradox of the darkening planet and the Earth’s climate sensitivity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7393, https://doi.org/10.5194/egusphere-egu23-7393, 2023.

X5.230
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EGU23-17500
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ECS
Harpreet Kaur, Govindasamy Bala, and Ashwin Sheshadri

Several previous studies have shown that the climate sensitivity (global mean temperature change per unit global mean radiative forcing) to external forcing is larger for forcing that is concentrated in higher latitudes than in lower latitudes. This is due to differences in radiative feedback processes accompanying the surface temperature change and amplifying the climate change.  The present study investigates the cause for the larger climate sensitivity to radiative forcing imposed in polar regions as compared to lower latitudes using a climate modelling framework. We use the NCAR CAM4 model coupled to a slab ocean model and make a systematic quantitative comparison of the individual climate feedbacks (water vapor, Planck, lapse rate, albedo, and cloud) for three experiments in which we increase the solar insolation separately in three latitude bands:  60°N to 90°N (Arctic case), 20°S to 20°N (Tropical case), and 90°S to 60°S (Antarctic case). The global mean radiative forcing is nearly the same (~4.1 Wm-2) in the three cases. Our results show that the climate sensitivity, which varies inversely with the feedback parameter, is nearly twice and thrice the tropical case for the Arctic and Antarctic cases, respectively. The differences arise mostly due to water vapor, lapse rate, and cloud feedbacks, which vary significantly in the three cases (Table 1). Planck feedback does not vary much among the cases (-2.77, -3.05, -2.81 Wm-2K-1 for the Arctic, Tropical, and Antarctic simulation, respectively), but the albedo feedback is twice for the Arctic (0.5 Wm-2K-1) case when compared to the  tropical (0.23 Wm-2K-1) and Antarctic (0.20 Wm-2K-1) cases. Understanding climate response to latitudinally varying radiative forcing patterns is valuable for understanding the effects of solar radiation modification (SRM) techniques which have been proposed as a potential option to offset global warming effects of increased atmospheric CO2 concentrations. Our study indicates that the lapse rate, water vapor, and cloud feedbacks, and hence the total climate sensitivity, could strongly depend on the region of changed insolation in SRM approaches.

 

Table 1. The annual average effective radiative forcing, global average surface temperature change, climate sensitivity (calculated as the ratio of surface temperature change and the radiative forcing), the albedo, Planck, lapse rate, water vapor, and cloud feedbacks for the ‘Arctic’, ‘Tropical’, and ‘Antarctic’ experiments. The baseline simulation is a  preindustrial simulation with a CO2 concentration of 284.7 ppm and solar constant of 1361 W m-2.

 

Arctic

Tropical

Antarctic

Radiative forcing (Wm-2)

4.16

4.17

4.05

Surface temperature change (K)

4.04

1.74

5.14

Climate sensitivity (K/Wm-2)

0.97

0.42

1.27

Albedo feedback (Wm-2K-1)

0.51

0.23

0.20

Planck feedback (Wm-2K-1)

-2.79

-3.07

-2.82

Lapse rate feedback (Wm-2K-1)

0.38

-0.93

0.01

Water vapor feedback (Wm-2K-1)

0.92

1.86

1.01

Cloud feedback (Wm-2K-1)

0.16

-0.41

0.38

 

How to cite: Kaur, H., Bala, G., and Sheshadri, A.: Why is climate sensitivity to polar radiative forcings larger than to tropical radiative forcings, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17500, https://doi.org/10.5194/egusphere-egu23-17500, 2023.

X5.231
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EGU23-11010
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ECS
Hee-Jeong Park and Sang-Wook Yeh

The increasing of atmospheric CO2 concentration due to human activities accelerates a warming rate and causes extreme climate events. The atmospheric-terrestrial biosphere carbon cycle is important for achieving the Paris agreement warming target and carbon neutrality with net zero emission. To understand the ecosystem carbon cycle, the Earth system model (ESM) is developed. However, there is a large inter-model uncertainty among ESMs thus reducing this uncertainty through understanding the relationship between atmospheric CO2 concentration and the terrestrial biosphere carbon cycle is important for reliable climate projection. Here, we investigate the impacts of inter-model differences in CO2 concentration over the East Asia on terrestrial carbon cycle using multi-ESMs. There is a larger uncertainty CO2 concentration in ESMs during historical period (1950-2014). To investigate impact of inter-model difference of CO2 concentration in ESMs on terrestrial vegetation in East Asia, we analyze emission-driven historical simulation in CMIP6 by classifying ESMs into two groups based on the averaged CO2 concentration in East Asia. The results show that inter-model difference of CO2 concentration in East Asia is associated with the carbon fertilization effect. ESMs with high CO2 concentration tend to simulate promoted vegetation activity. Furthermore, we analyze the relationship between CO2 concentration, terrestrial biosphere, and climate factors.

How to cite: Park, H.-J. and Yeh, S.-W.: Understanding the impacts of inter-model difference in atmospheric CO2 concentration on terrestrial vegetation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11010, https://doi.org/10.5194/egusphere-egu23-11010, 2023.

X5.232
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EGU23-2271
Hylke Beck, Tim McVicar, Noemi Vergopolan, Alexis Berg, Nicholas Lutsko, Ambroise Dufour, Zhenzhong Zeng, Xin Jiang, Albert van Dijk, and Diego Miralles

We present Version 2 of our widely used 1-km Köppen-Geiger climate classification maps for historical and future climate conditions. The historical maps (1901–1930, 1931–1960, 1961–1990, 1991–2020) are based on high-resolution, observation-based climatologies, while the future maps (2041–2070 and 2071–2099) are based on downscaled and bias-corrected climate projections for seven shared socio-economic pathways (SSPs). We evaluated 64 climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6) and kept a subset of 40 with the most plausible CO2-induced warming rates. Under the “middle of the road” scenario SSP2-4.5, the global land surface area (excluding Antarctica) with suitable climatic conditions for tropical, arid, temperate, cold, and polar vegetation is projected to show a net change of +9 %, +3 %, 3 %, 2 %, 33 %, respectively, in 2071–2099 (with respect to 1991–2020). The Köppen-Geiger maps, including associated confidence estimates, the underlying monthly air temperature and precipitation data, and sensitivity metrics for CMIP6 climate models are available at www.gloh2o.org/koppen.

How to cite: Beck, H., McVicar, T., Vergopolan, N., Berg, A., Lutsko, N., Dufour, A., Zeng, Z., Jiang, X., van Dijk, A., and Miralles, D.: High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections for seven socio-economic scenarios, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2271, https://doi.org/10.5194/egusphere-egu23-2271, 2023.

X5.233
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EGU23-14962
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ECS
Shabehul Hasson, Benjamin Stuch, Ellen Kynast, Jürgen Böhner, Rüdiger Schaldach, and Hermann Jungkunst

The Amazon rainforest is globally relevant and is considered a tipping element in the global climate system. Studies suggest that deforestation in the Amazon by around 30% may disturb regional convective rain patterns, which could increase drought frequencies and intensities locally and, may activate a cascade of tipping elements in the global climate system. Here, we aim to assess the relationship between deforestation and climate responses at a convection-permitting scale by employing a non-hydrostatic mesoscale Weather Research and Forecasting (WRF) model. For this, we first developed a spatially explicit deforestation model for the South-Western Amazon to see an effect of deforestation intensity ranging from 10% to 60%, and then based on 30% deforestation, we further see the role of deforestation pattern (e.g. deforestation alongside the roads, as a large single or small multiple circular plots, and their geographical positions), and shifts to anticipated land use. Then for each deforestation map, we simulate the land-atmosphere interactions and responses in the regional rainfall and temperatures by dynamically downscaling the ERA5 reanalysis using WRF for the year 2020 at 5km spatial resolution and by explicitly resolving convection. We assess non-linearity in the land-climate interaction to different combinations of deforestation quantities and deforestation patterns. Our preliminary results show a general pattern of decreasing mean and extreme rainfall with deforestation where the geographical location and the pattern of deforestation also play a role. The study will provide an insight into whether the employed quantitative methods are able, or good enough, to simulate relevant processes between the biosphere and the atmosphere that could promote assessing tipping points in the Amazon.

How to cite: Hasson, S., Stuch, B., Kynast, E., Böhner, J., Schaldach, R., and Jungkunst, H.: Tipping the Amazon Rainforest: Regional deforestation and land-climate interactions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14962, https://doi.org/10.5194/egusphere-egu23-14962, 2023.

X5.234
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EGU23-17454
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Julian Newman and Peter Ashwin

Rate-induced phenomena can be mathematically modelled in terms of a dynamical system with a real-time (as opposed to quasistatic) parameter drift between two values; that is to say, the parameter converges to two different values as time tends to negative and positive infinity, giving rise to a nonautonomous dynamical system that is asymptotically autonomous. Representing stable climate states by attractors of the parameter-dependent autonomous system through which the parameter drift takes place, rate-induced tipping is modelled as the phenomenon that a trajectory of the nonautonomous system that starts in the past in the vicinity of one attractor lands in the vicinity of an attractor representing a different stable climate state in the future. However, if these attractors are chaotic, they exhibit sensitive dependence on initial conditions, which on the one hand makes investigation of any individually selected typical initial condition numerically impossible and physically irrelevant, but on the other hand makes a probabilistic description of long-term behaviour of trajectories an effective tool. This probabilistic description is provided by the "natural measure" on a chaotic attractor; in this poster, we consider the question of when this concept of "natural measures" can be extended from the classical setting of autonomous systems to the setting of asymptotically autonomous systems and hence used to provide a mathematically well-defined quantification of the "probability of tipping" between two stable climate states.

How to cite: Newman, J. and Ashwin, P.: Natural measures of asymptotically autonomous systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17454, https://doi.org/10.5194/egusphere-egu23-17454, 2023.

Posters virtual: Tue, 25 Apr, 08:30–10:15 | vHall CL

Chairpersons: Ruth Chapman, Paul Ritchie
vCL.12
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EGU23-17519
Chris Huntingford, Peter Cox, Paul Rithie, Joe Clarke, and Mark Williamson

We analyse a large number of Earth System Models (ESMs) and find that there is some evidence that the temperatures of extreme events are rising faster than local background rises in mean summer temperatures. We find this to be true for almost all land regions when analysing the SSP585 scenario and for the decades from now until the end of the 21st Century. We find strong correlations between the level of acceleration and upward trends in sensible heat fluxes. In the few tropical regions where there is less correlation, we instead find a link to background latent plus sensible heat, which acts as a proxy for overall available energy. We then study extreme acceleration in the contemporary period, in both ESMs and ERA5 data. We find in these circumstances particularly strong evidence of faster warming of extreme events, but only for selected regions. We suggest this is a consequence of highly regional effects such as aerosols. Our analysis hints that as atmospheric composition changes move towards alteration by greenhouse gases only, there will be a more general globally-applicable occurrence of high-temperature extremes, with their mean increase more than the more general background warming levels.  

How to cite: Huntingford, C., Cox, P., Rithie, P., Clarke, J., and Williamson, M.: Acceleration of Daily Land Temperature Extremes and Link to Land Forcing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17519, https://doi.org/10.5194/egusphere-egu23-17519, 2023.

vCL.13
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EGU23-497
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ECS
yongxiao liang, Nathan Gillett, and Adam Monahan

Observational constraint methods based on emergent relationships between observable predictors and future projected warming across multi-model ensembles enable us to constrain multi-model projections. Unforced internal variability in predictors can weaken such emergent relationships. Assessing the Sixth Coupled Model Intercomparison Project (CMIP6) with all accessible realizations, we find that there of sea surface temperature (SST) trend over the eastern tropical pacific (ETP) which is well correlated with the global warming trend. The strong cooling in the ETP in observations induces a global-scale cooling, yet most realizations in the CMIP6 multi-model ensemble cannot reproduce it. Using the observed raw historical global mean near surface air temperature (GSAT) trend as a constraint therefore results in a relatively lower projected 21st century warming. However, by removing the unforced internal variability associated with variation in the ETP in observed and simulated GSAT trends, we find an enhanced correlation between GSAT trends and projected warming and improved results in an imperfect model test. This approach results in a relatively higher 21st century warming than a constrained projection based on the raw GSAT trend, and brings constrained projections into much closer agreement with projections constrained using climatological cloud metrics.

How to cite: liang, Y., Gillett, N., and Monahan, A.: Narrowing uncertainties in projected warming by constraining using the past global warming trend with the pattern effect removed, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-497, https://doi.org/10.5194/egusphere-egu23-497, 2023.

vCL.14
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EGU23-17341
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ECS
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Isobel Parry, Paul Ritchie, and Peter Cox

Amazon forest dieback is seen as a potential tipping point under climate change. These concerns are partly based-on an early coupled climate-carbon cycle simulation that produced unusually strong drying and warming in Amazonia. In contrast, the 5th generation Earth System Models (CMIP5) produced few examples of Amazon dieback under climate change. This presentation examines the results from seven 6th generation models (CMIP6) which include interactive vegetation carbon, and in some cases interactive forest fires. Although these models typically project increases in area-mean forest carbon across Amazonia under CO2-induced climate change, five of the seven models also produce abrupt reductions in vegetation carbon which indicate localised dieback events. The Northern South America region (NSA), which contains most of the rainforest, is especially vulnerable in the models. These dieback events, some of which are mediated by fire, are preceded by an increase in the amplitude of the seasonal cycle in near surface temperature, which is consistent with more extreme dry seasons. Based on the ensemble mean of the detected dieback events we estimate that 7+/-5% of the NSA region will experience abrupt downward shifts in vegetation carbon for every degree of global warming past 1.5°C.

How to cite: Parry, I., Ritchie, P., and Cox, P.: Evidence of localised Amazon rainforest dieback in CMIP6 models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17341, https://doi.org/10.5194/egusphere-egu23-17341, 2023.